{"id":"https://openalex.org/W4415708518","doi":"https://doi.org/10.1109/icme59968.2025.11209456","title":"Lightweight Learning-Based In-Loop Filter for Real-Time Video Coding","display_name":"Lightweight Learning-Based In-Loop Filter for Real-Time Video Coding","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4415708518","doi":"https://doi.org/10.1109/icme59968.2025.11209456"},"language":null,"primary_location":{"id":"doi:10.1109/icme59968.2025.11209456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001124113","display_name":"Yanchen Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanchen Zhao","raw_affiliation_strings":["Peking University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089552911","display_name":"Wenhong Duan","orcid":"https://orcid.org/0000-0002-6835-3270"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhong Duan","raw_affiliation_strings":["Peking University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100349810","display_name":"Jiaqi Zhang","orcid":"https://orcid.org/0000-0001-7040-704X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqi Zhang","raw_affiliation_strings":["Peking University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031637081","display_name":"Zhimeng Huang","orcid":"https://orcid.org/0000-0001-8026-9349"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimeng Huang","raw_affiliation_strings":["Peking University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science,China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317809","display_name":"Lian Li","orcid":"https://orcid.org/0000-0003-4700-1134"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin Li","raw_affiliation_strings":["Migu Culture Technology Co., Ltd.,China"],"affiliations":[{"raw_affiliation_string":"Migu Culture Technology Co., Ltd.,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016337133","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0001-8260-3574"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["MIGU Video Co., Ltd.,China"],"affiliations":[{"raw_affiliation_string":"MIGU Video Co., Ltd.,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039832462","display_name":"Siwei Ma","orcid":"https://orcid.org/0000-0002-2731-5403"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Siwei Ma","raw_affiliation_strings":["Peking University,School of Computer Science,China"],"affiliations":[{"raw_affiliation_string":"Peking University,School of Computer Science,China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":7,"corresponding_author_ids":["https://openalex.org/A5001124113"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.39278928,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10741","display_name":"Video Coding and Compression Technologies","score":0.8877999782562256,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10741","display_name":"Video Coding and Compression Technologies","score":0.8877999782562256,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.029200000688433647,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.015300000086426735,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6488000154495239},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6126000285148621},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6114000082015991},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4555000066757202},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4514999985694885},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.3880000114440918},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35429999232292175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7519999742507935},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6488000154495239},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6126000285148621},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6114000082015991},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48410001397132874},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4514999985694885},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3644999861717224},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C101722063","wikidata":"https://www.wikidata.org/wiki/Q218825","display_name":"Random access","level":2,"score":0.3294000029563904},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3262999951839447},{"id":"https://openalex.org/C190750250","wikidata":"https://www.wikidata.org/wiki/Q13533439","display_name":"Coding tree unit","level":3,"score":0.31949999928474426},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.3084000051021576},{"id":"https://openalex.org/C184670325","wikidata":"https://www.wikidata.org/wiki/Q512604","display_name":"Loop (graph theory)","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2939000129699707},{"id":"https://openalex.org/C116709606","wikidata":"https://www.wikidata.org/wiki/Q1296251","display_name":"Algorithmic efficiency","level":3,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme59968.2025.11209456","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme59968.2025.11209456","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1964671510","https://openalex.org/W1966156115","https://openalex.org/W1980275325","https://openalex.org/W2098768521","https://openalex.org/W2130673281","https://openalex.org/W2142536989","https://openalex.org/W2146395539","https://openalex.org/W2891639355","https://openalex.org/W2943766642","https://openalex.org/W2968469126","https://openalex.org/W2999940418","https://openalex.org/W3010897794","https://openalex.org/W3013522332","https://openalex.org/W3134368609","https://openalex.org/W3152708635","https://openalex.org/W3153323090","https://openalex.org/W3153617831","https://openalex.org/W3168057692","https://openalex.org/W3183509111","https://openalex.org/W3202918664","https://openalex.org/W4214890647","https://openalex.org/W4220715488","https://openalex.org/W4230027440","https://openalex.org/W4385453475","https://openalex.org/W4386230923","https://openalex.org/W4400111335","https://openalex.org/W4401878721","https://openalex.org/W4406858935","https://openalex.org/W4406860160"],"related_works":[],"abstract_inverted_index":{"In":[0],"recent":[1],"years,":[2],"video":[3],"coding":[4,15,65,135],"tools":[5,23,88],"based":[6],"on":[7,164],"neural":[8,19,43,50,84,115],"networks":[9],"have":[10],"emerged":[11],"continuously,":[12],"showing":[13],"remarkable":[14],"performance.":[16],"Especially":[17],"the":[18,26,60,64,80,111,155,165,170],"network-based":[20,44,51,85,116],"loop":[21,52,86,117],"filter":[22],"are":[24,76],"currently":[25],"hottest":[27],"research":[28],"direction":[29],"in":[30,63,106,119,134],"both":[31],"standard":[32],"development":[33],"and":[34,47,147,161],"academic":[35],"research.":[36],"Compared":[37],"to":[38],"other":[39],"directions,":[40],"such":[41],"as":[42,59,79],"intra":[45],"prediction":[46],"inter":[48],"prediction,":[49],"filtering":[53,87,118],"shows":[54],"significant":[55,132],"performance":[56,136],"improvements.":[57],"Moreover,":[58],"final":[61],"step":[62],"loop,":[66],"it":[67],"is":[68,89],"advantageous":[69],"for":[70],"hardware":[71],"implementation.":[72],"However,":[73],"its":[74],"disadvantages":[75],"also":[77],"evident,":[78],"computational":[81],"complexity":[82],"of":[83,98,113,142,179],"extremely":[90],"high,":[91],"often":[92],"requiring":[93],"hundreds":[94],"or":[95],"even":[96],"thousands":[97],"kilo":[99],"Multiply-Accumulate":[100],"operations":[101],"(kMACs)":[102],"per":[103],"pixel.":[104],"Therefore,":[105],"this":[107],"paper,":[108],"we":[109],"explore":[110],"possibility":[112],"applying":[114],"real-time":[120,167],"codec.":[121,168],"We":[122],"propose":[123],"a":[124],"Lightweight":[125],"Learning-Based":[126],"In-Loop":[127],"Filter":[128],"(LLILF)":[129],"which":[130],"achieves":[131,173],"improvement":[133],"with":[137],"minimal":[138],"complexity.":[139],"It":[140],"consists":[141],"only":[143],"two":[144],"convolutional":[145],"layers":[146],"has":[148],"153":[149],"parameters.":[150],"Experimental":[151],"results":[152],"show":[153],"that":[154],"proposed":[156,171],"method":[157],"can":[158],"achieve":[159],"1080p@30fps":[160],"720p@60fps":[162],"encoding":[163],"SVT-AVS3":[166,182],"Additionally,":[169],"network":[172],"an":[174],"average":[175],"BD-rate":[176],"(VMAF)":[177],"saving":[178],"15.35%":[180],"over":[181],"under":[183],"Random":[184],"Access":[185],"(RA)":[186],"configuration.":[187]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-30T00:00:00"}
